A. W. Wood
- ORCiD
- https://orcid.org/0000-0002-6231-0085
- OpenAlex ID
- https://openalex.org/A5038525681 (API record)
Associated Concepts [?]
- Environmental science
- Geology
- Geography
- Physics
- Climatology
- Computer science
- Meteorology
- Engineering
- Biology
- Cartography
- Ecology
- Mathematics
- Drainage basin
- Oceanography
- Geotechnical engineering
- Statistics
- Economics
- Precipitation
- Streamflow
- Hydrology (agriculture)
- Philosophy
- Quantum mechanics
- Climate change
- History
- Geomorphology
Authored Works
sorted by decreasing year, and then by display-name
- Improving the prediction of precipitation, snowpack and streamflow in mountainous basins through ensemble-based variable-complexity watershed modeling
- A new process-oriented ensemble hydrological prediction system for flood prediction and water management in the US Pacific Northwest
- Using multi-scale SUMMA watershed modeling for seasonal streamflow prediction to support water operations at Buffalo Bill Reservoir, Wyoming
- The Next Generation Water Resources Modeling Framework: Open Source, Standards Based, Community Accessible, Model Interoperability for Large Scale Water Prediction
- Quantifying uncertainty in regional precipitation projections and using data driven approaches to identify process errors
- Next Generation National Water Model: Strategy and Preliminary Performance of Initial Model Formulations
- Merging Airborne Snow Data with Long-term Hydrometeorological Observations to Improve Water Supply Forecasting
- Extensions to the Basic Model Interface to Support Serialization of a Model's State Variables for Load Balancing and Checkpointing
- Earth System Science Advances are Outpacing their Uptake for Informing Adaptation Actions: How can We do Better?
- Community modeling: supporting large-domain water resources modeling through an open-source model configuration toolbox
- Assessing seasonal streamflow forecast strategies for Upper Rio Grande basin water management using SUMMA watershed models
- An updated vegetation dataset increases previous runoff projections in the Colorado River Basin
- An Enhanced Noah-MP for Nextgen: Modularization and Implementation of the Basic Model Interface
- Advancing the science and practice of community hydrologic modeling: Development of open-source models, methods, and datasets to enable process-based hydrologic prediction across North America (and beyond)
- Advances in land surface modeling and prediction frameworks and tools to support risk-based national-scale water and emergency management
- A snow modeling and water prediction testbed for benchmarking the water resources impacts of Earth Observations in North America
- A benchmark for probabilistic seasonal streamflow forecasting across North America
Linked Co-Authors
- Abigail M. Smith
- Andrew Bennett
- Andrew J. Newman
- Bart Nijssen
- Brian Avant
- Chris Frans
- Christopher B. Marsh
- David G. Tarboton
- E. D. Gutmann
- Ethan T. Coon
- Flavio Lehner
- Guoqiang Tang
- Hongli Liu
- Jonathan Frame
- Joseph Hamman
- K. S. Jennings
- Louise Arnal
- Martyn P. Clark
- Paul H. Whitfield
- Raymond J. Spiteri
- S. D. Peckham
- S. Papalexiou
- Shervan Gharari
- Vimal Mishra
- Vincent Fortin
- Vincent Vionnet
- William Ryan Currier
- Wouter Knoben
Linked Collaborating Institutions
- Army Corps of Engineers
- California State University, Monterey Bay
- Colorado School of Mines
- Cornell University, New York
- Environment Canada
- Indian Institute of Technology, Delhi, India
- Indian Institute of Technology, Gandhinagar
- Los Alamos National Laboratory, New Mexico
- National Center for Atmospheric Research, Colorado
- National Oceanic and Atmospheric Administration, Boulder
- National Oceanic and Atmospheric Administration, Washington
- Oak Ridge National Laboratory, Tennessee
- United States Army
- University Corporation for Atmospheric Research, Colorado
- University of Alabama, Tuscaloosa
- University of Arizona
- University of Colorado, Boulder
- University of Saskatchewan, Canada
- University of Washington, Seattle
- Utah State University
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